Locomotion dynamics of hunting in wild cheetahs

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Abstract

Although the cheetah is recognised as the fastest land animal, little is known about other aspects of its notable athleticism, particularly when hunting in the wild. Here we describe and use a new tracking collar of our own design, containing a combination of Global Positioning System (GPS) and inertial measurement units, to capture the locomotor dynamics and outcome of 367 predominantly hunting runs of five wild cheetahs in Botswana. A remarkable top speed of 25.9 m s(-1) (58 m.p.h. or 93 km h(-1)) was recorded, but most cheetah hunts involved only moderate speeds. We recorded some of the highest measured values for lateral and forward acceleration, deceleration and body-mass-specific power for any terrestrial mammal. To our knowledge, this is the first detailed locomotor information on the hunting dynamics of a large cursorial predator in its natural habitat.

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Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges.

Francesca Cagnacci, Luigi Boitani, Roger A. Powell … (2010)

Global positioning system (GPS) telemetry technology allows us to monitor and to map the details of animal movement, securing vast quantities of such data even for highly cryptic organisms. We envision an exciting synergy between animal ecology and GPS-based radiotelemetry, as for other examples of new technologies stimulating rapid conceptual advances, where research opportunities have been paralleled by technical and analytical challenges. Animal positions provide the elemental unit of movement paths and show where individuals interact with the ecosystems around them. We discuss how knowing where animals go can help scientists in their search for a mechanistic understanding of key concepts of animal ecology, including resource use, home range and dispersal, and population dynamics. It is probable that in the not-so-distant future, intense sampling of movements coupled with detailed information on habitat features at a variety of scales will allow us to represent an animal's cognitive map of its environment, and the intimate relationship between behaviour and fitness. An extended use of these data over long periods of time and over large spatial scales can provide robust inferences for complex, multi-factorial phenomena, such as meta-analyses of the effects of climate change on animal behaviour and distribution.